Automated industrial inspection and process monitoring technologies have often presented a substantial set up and optimization challenge. In automated or semi-automated high production factory environments, automated inspection technologies may be incorporated to monitor a wide range of product or process attributes. Many requirements are highly definable such as dimensions, number and location of holes, shape, thread pitch, and the like. These quantitative values are more easily set with a-priori knowledge, prior to production. Other types of product or process attributes are much more subjective and often cannot be easily quantified, measured, or specified prior to starting production. These tend to be related to variations of the raw materials or the production process itself. A few examples might be the size of a dip in a sealant compound, the sound quality of a child's talking toy, blotchiness of a mat surface, or the blurriness of an image. There are thousands of examples of these subjective attributes that must be monitored in manufacturing environments on an on-going basis. While it is possible to quantize each of them in a laboratory, the on-line monitoring systems are often less sensitive and designed to be more practical to function at real time, on-line speeds. While there is typically some kind of written specification there is generally a substantial amount of judgmental subjectivity in the interpretation of the specification on the plant floor. It is not unusual for a plant manager and a quality control manager to have substantial disagreement as to the suitability for shipment of a particular batch of product.
The practicality of increasing revenue shipments will often win over the more idealistic requirement of shipping a more perfect product. Sometimes, the level of quality expectation is cultural and has its' direct effect on quality expectations in a particular region. Other times, it is dictated by the quality standards and expectations of the buyer. Still other times, the end consumer of the product will dictate the final level of quality as a function of what the market is willing to pay for the product. All of these different quality expectations combine with the inherent quality challenge of a particular process or raw material lead to a need to dictate the automated inspection or process monitoring levels in accordance with the current need.
There are many reasons why process monitoring or inspection quality levels may need to be modulated but it is well established that this need exists in hundreds of thousands of converting and manufacturing plants around the world. The subject invention is a graphical methodology to allow for a more user-friendly and more intuitive way of understanding and changing such parameters.
As the inspection or monitoring parameters are changed, an immediate question often becomes “what will the revenue effect be of such a change?” The change of a quality threshold will usually mean that a different quantity of product will be either scrapped or sent for rework or recycling. Therefore, this decision to make the change in the quality level has a direct financial impact. Whoever is responsible for making such change will usually want to have the most direct feedback possible of what kind of revenue or financial impact such change may make. The subject invention facilitates an immediate understanding or could provide data which will lead to a quick understanding of financial and other impact to such a change.
A purist might argue that improved quality level would pay for itself. To the extent that this is true, the subject invention facilitates a much better understanding of the subtleties of changing the settings and it makes the settings on the basis of a large population of product rather than on a few individual samples.
It is also possible to use the subject invention to close a range of different process loops in either a manual, semi-automatic, or automatic way. The invention can be interconnected with another machine so that the indicator values can be associated with specific machine data at time of manufacture of a specific product. The melding of a complete record of each part can facilitate closing the loop with closely coupled machines so that a process can be continually optimized. Ease of understanding the inspection process interrelationship by virtue of the graphical user interface can facilitate closing control loops with a high confidence level.
The subject invention is adaptable to a wide-range of different industrial inspection and process monitoring systems. An abbreviated list follows:                Gray scale machine vision inspection or process monitoring systems        Color based machine vision inspection or process monitoring systems        X-ray based machine vision inspection or process monitoring systems        Thermal infra-red vision inspection or process monitoring system        Integrated mass inspection or process monitoring systems        Acoustic signature inspection or process monitoring systems        Force or pressure signature inspection or monitoring systems        Spectophotometric inspection or monitoring systems        Ultrasonic imaging inspection or process monitoring systems        Ultrasonic signature inspection or process monitoring systems        Profilometer inspection or process monitoring systems        Surface finish inspection or process monitoring systems        Glossometers inspection or process monitoring systems        Laser interferrometric inspection or process monitoring systems        Dimensional inspection or process monitoring systems        Scanning laser inspection or process monitoring systems        Densitometer inspection or process monitoring systems        Thermal signature inspection or process monitoring systems        Pattern inspection or process monitoring systems        
The above list is a partial one and the system types are cited by way of example. It should be understood that the subject invention can function as a user interface “front end” for nearly any system which has adjustable parameters or thresholds, the results of which needs to be dynamically understood on a sizeable historical sample set while changing them.